Data Science Manager, Security Compliance Engineering, Stores Security

About the role

Security is moving from something builders stop for to something that runs quietly inside how they already work: guidance that shows up in their tools as they code, and continuous checks that replace the weeks-long review queue. Behind that shift is data. Knowing which controls a service actually needs, surfacing where real risk lives across a massive portfolio, whether the guidance we give is accurate enough to trust, and whether any of it is genuinely reducing risk. You'll lead the data science and data engineering team that answers those questions and makes that whole model measurable.

Proving efficacy at scale is where you'll have the biggest impact. It's easy to ship guidance, but hard to know it's working: that it's accurate, that builders act on it, that fewer issues reach production because of it. You'll own the data that turns those into answers leaders can act on, and the feedback loop that uses every issue we find to make the guidance smarter so the same problem never recurs.

You'll be the leader who gets the craft of data scientists, data engineers, and business intelligence engineers, and can bring them together as one group with a shared direction. You'll set the vision, raise the technical bar, and build the foundations good science depends on: trusted data, reliable pipelines, and reproducible research.

You'll love this role if you enjoy:

- Turning security from a gate into a default, and proving with data that the shift actually works.

- Finding where risk really lives, using data and models to surface the issues and high-risk code that matter most before they reach production.

- Answering hard measurement questions at scale: is our guidance accurate, are builders acting on it, are fewer issues reaching production?

- Working across disciplines, using science, analytics, and engineering together so each makes the others stronger.

- Standing up something new: shaping the strategy, culture, and standards for a team ready for its first dedicated data leader.

- Growing engineers and scientists and watching them take on bigger scope because of how you invested in them.

Key job responsibilities

- Set the strategy, roadmap, and technical direction for a combined data science and data engineering team, turning an ambiguous, fast-moving security mission into clear, prioritized work and partnering with tech and business leadership to shape the vision.

- Own how we measure whether embedded security is working: build the metrics, experiments, and analysis that show whether guidance is accurate, whether builders act on it, and whether fewer issues reach production because of it.

- Lead the data science behind risk identification and the compounding feedback loop: surface where real risk lives across a large portfolio, scope which controls each service needs, and make sure every issue found feeds back into smarter guidance so the same problem does not recur.

- Determine the right mix of science, data engineering, and BI resources, use those disciplines to complement rather than duplicate one another, and lead senior individual contributors credibly across both the science and engineering sides of the team.